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Found 362 Skills
Deployment & Operations Expert responsible for securely, rollbackable, and observably deploying builds that pass Reviewer and QA gates to servers (PM2 3-process cluster + Nginx reverse proxy + BT Panel). Adheres to engineering baselines including zero-downtime deployment, health checks, rollback within ≤3 minutes, and post-release smoke testing. Handles deployment orchestration, configuration management, traffic management, and monitoring & alerting. Applicable when receiving task cards from the Deploy department or needing to release to production.
Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation. Orchestration runs inline in main flow (no separate orchestrator agent). Supports continuous iteration with markdown progress documentation. Triggers on "parallel-dev-cycle".
Docker containerization expert: Dockerfile optimization, multi-stage builds, security hardening, Docker Compose orchestration, and production deployment. Use for Dockerfile creation/review, image size issues, container security, networking, and orchestration.
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration. Use when the user asks about LLM monitoring, GenAI observability, or AI cost/quality.
Install and use the Edict (三省六部) multi-agent orchestration system with 12 specialized AI agents, real-time kanban dashboard, and audit trails
Python port of Claude Code agent harness — tools, commands, task orchestration, and CLI entrypoint via oh-my-codex
Expert knowledge for Azure Functions development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building HTTP/queue/event-triggered Functions, Durable orchestrations, containerized Functions, CI/CD, or Dapr/OpenAI integrations, and other Azure Functions related development tasks. Not for Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).
DataWorks data development Skill. Create, configure, validate, deploy, update, move, and rename nodes and workflows. Manage components, file resources, and UDF functions. Covers 150+ node types: Shell, SQL, Python, DI, Flink, EMR, etc. Supports scheduled and manual workflow orchestration via aliyun CLI or Python SDK. WARNING: Supports mutating operations (Move, Rename) requiring explicit user confirmation. Delete operations are NOT supported by this skill. Triggers: DataWorks, data development nodes, workflows, FlowSpec, scheduling tasks, data integration, ETL pipelines, .spec.json. Also triggers for Alibaba Cloud data development, scheduling node configuration, FlowSpec format, or DI task orchestration.
Vercel Workflow DevKit (WDK) expert guidance. Use when building durable workflows, long-running tasks, API routes or agents that need pause/resume, retries, step-based execution, or crash-safe orchestration with Vercel Workflow.
Use when you need multi-agent orchestration for OpenAI Codex CLI. Triggers on: omx, $plan, $ralph, $team, $autopilot, $deep-interview. v0.11.10 — 30+ agents, 35+ workflow skills, tmux team runtime, sparkshell, explore, ralplan.
Use when you need Teams-first multi-agent orchestration in Claude Code. Triggers on: omc, autopilot, ralph, ulw, ccg, team. 29+ specialized agents, smart model routing (Haiku→Opus), persistent execution loops, skill layers, real-time HUD.
Integrated AI agent orchestration skill that combines plannotator, ralphmode, team or bmad execution, agent-browser verification, and agentation feedback loops, while maintaining a project-local `.jeo` ledger for planning, development, and QA. Use when the user wants an end-to-end multi-agent workflow with plan approval, implementation, UI review, cleanup, and durable task history. Triggers on: jeo, annotate, ui-review, multi-agent orchestration.